Based on the RSSI values, we found that there are distinctive features of data that can be utilized as flags for classifying the three above conditions. The RSSI measurement was repeatedly conducted for three different conditions, in an empty room, with the presence of a single intruder and the presence of multiple intruders. With a suitable coordinate of sensor nodes, a WSN telemetry could be established to minimize the blind spot area and limit the movement of the intruder with a minimum area of 0.2 m2. The system was developed using 20 of ESP8266-12F Wi-Fi modules transmitters and another 2 of ESP8266-12F as the access points located in 3 m × 3 m area of interest.
Instead of using closed-circuit television as the existing security platform, this indoor safety system was improved with a convenient, cheap, and low-power solution. This paper presents an analysis of the received signal strength indicator (RSSI) from the radio frequency signals for human identification in an indoor wireless sensor network (WSN).
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